The dream of watching a protein function in real time with near atomic resolution has been realized using picosecond time-resolved Laue crystallography, an experimental methodology first developed by the Anfinrud group at the ESRF in Grenoble, France. To advance this capability further, we initiated a major effort to develop the infrastructure required to pursue picosecond time-resolved X-ray science at the Advanced Photon Source (APS) in Argonne, IL. This effort, which was initiated in 2005, is summarized in a separate report. One of the critical components in this effort is TReX, an in-house software package designed to analyze time-resolved Laue data. This effort has proven to be much more demanding than envisioned at the outset, but represents a critical component in our research. We are currently overcoming remaining issues and are working on a major update to this software package: TReX-II. The first step in analyzing crystal diffraction data, whether acquired with monochromatic or polychromatic X-ray radiation, is the indexing of diffraction spots recorded on a two-dimensional detector. Robust auto-indexing algorithms have long existed for monochromatic diffraction images, but Laue diffraction images, which are generated with a polychromatic X-ray source, are not amenable to those methods. Consequently, the analysis of Laue diffraction data was a time-consuming, off-line process that required a significant amount of face time in front of a computer. To address this problem, a robust zone-based algorithm for auto-indexing Laue diffraction images was developed by Dr. Eric Henry. When the image center and distance between the sample and the detector are prescribed, spots on the detector plane can be mapped onto a locus of possible zone-vector directions, the consensus of which identifies zone-vectors suitable for determining the orientation of the crystal. As an added benefit, zone-vector consensus provides a criterion for optimizing the center of the detector, knowledge of which is crucial to accurately predict the Laue diffraction pattern. Once the Laue pattern is predicted, the spot intensities need to be integrated, scaled, and merged with results from numerous crystal orientations. Finally, the merged results are Fourier transformed to generate time-resolved electron density maps. The integration methods employed by our group thus far are derivative of PROW, a software package developed by Dr. Dominique Bourgeois for PRofile integration of Overlapping and Weak spots. We have discovered that the precision and accuracy of the integration suffers from numerous systematic errors;these errors contribute much noise to the diffraction data, and adversely affect the quality of electron density maps constructed from those data. These problems became apparent when analyzing data acquired using a novel protocol in which 37 diffraction images at time points spanning 100 ps to 100 ms with 4 time points per decade were collected at a single orientation with a single crystal. To minimize the extent of radiation damage, which would destroy the protein crystal if that many images were acquired from a single spot on the crystal, we translated the crystal stepwise along its length between exposure to single X-ray pulses, thereby distributing the radiation damage across the entire length of the crystal. This protocol requires long crystals, and was first tested using photoactive yellow protein crystals 0.6-mm in length. Examination of the spot intensities across the extensive time series unveiled numerous sources of systematic errors that compromise the accuracy of the integration methods currently employed by TReX. We are in the process of breaking away from PROW-based methods and are developing new integration and scaling methods that avoid the pitfalls that have plagued this and other Laue processing software packages. Once diffraction spots are integrated accurately, redundant observations from other orientations must be merged to assemble a data set that is as complete as experimentally feasible. Merging redundant Laue data requires both image scaling and wavelength normalization, each of which is error prone. Thus, the quality of Laue data has traditionally been inferior to data acquired with monochromatic methods. We are currently working on a ratio method that eliminates the need to scale redundant observations acquired at different orientations, as scaling is automatically accomplished by taking the ratio of laser on and laser off observations acquired in the time series. To that end, we acquire our time-resolved diffraction images with numerous reference images interleaved among them, and are developing interpolation schemes to ensure that the ratio is computed relative to the highest quality reference image possible. We have experimented with off images and negative-time images (where the x-ray pulse arrives in advance of the laser pulse) as reference images. From our studies thus far, we believe that negative-time images provide the best reference for taking ratios. The number of reference images acquired in a time series affects the ultimate signal-to-noise ratio of the data. Using the signal-to-noise ratio as the figure of merit, the optimal number of reference images is equal to the square root of the total number of images in the time series. Thus, a logarithmic time sequence with 37 time points should have 6 reference images interleaved among them. These reference images track the degradation of the crystal diffraction, and provide a reference against which the time-resolved data can be scaled. Though this approach is still a work in progress, we anticipate that electron density maps computed according to merged ratios will provide much greater structural detail than achieved in the past. A global analysis method developed by our group for processing time-resolved spectroscopic data has recently been extended to time-resolved electron density data. This method allows us to recover by linear least-squares methods time-independent electron density maps for each state in a kinetic model. The S/N ratio for these maps are enhanced relative to the individual snapshots in accordance with the number of time frames in which that structure is represented. Moreover, this approach allows us to refine rate coefficients for structural change. This methodology was first tested on a recently acquired PYP data set, and the results obtained for its trans to cis isomerization dynamics were very promising. Since then, we explored the suitability of this method for characterizing ligand migration in heme proteins, for which numerous structural states must be characterized. One of the challenges remaining is to quantify the absolute populations of the intermediates.